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1型糖尿病潜在治疗靶点的多组学研究。

Multi-omics investigation of prospective therapeutic targets for type 1 diabetes.

作者信息

Zhang Yue-Yang, Qiao Qing-Tian, Chen Bing-Xue, Wan Qin

机构信息

Department of Endocrinology and Metabolism, Affiliated Hospital of Southwest Medical University, Luzhou, China.

Metabolic Vascular Disease Key Laboratory of Sichuan Province, Luzhou, China.

出版信息

Ther Adv Endocrinol Metab. 2025 May 7;16:20420188251337988. doi: 10.1177/20420188251337988. eCollection 2025.

Abstract

BACKGROUND

In recent years, the incidence of type 1 diabetes has been rising steadily, positioning its prevention and treatment as a central focus of global public health initiatives. Previous Mendelian randomization (MR) studies have investigated the relationship between proteomics and type 1 diabetes. Consequently, this study aims to identify prospective therapeutic targets for type 1 diabetes through a comprehensive multi-omics analysis.

METHODS

This study primarily utilized the MR method, drawing on genetic data from several large-scale, publicly accessible genome-wide association studies. Within this framework, we applied two-sample MR to evaluate the relationship between five omics components and type 1 diabetes. Finally, we conducted various sensitivity analyses and bidirectional MR to ensure the robustness and reliability of our findings.

RESULTS

The inverse variance weighted method revealed that, following false discovery rate correction, 39 plasma proteins and 3 plasma protein ratios exhibited significant associations with type 1 diabetes. The genetically predicted risk of type 1 diabetes ranged from 0.05 for RBP2 to 394.51 for FMNL1. Furthermore, 4-chlorobenzoic acid levels demonstrated a potential association with type 1 diabetes.

CONCLUSION

Our research identified numerous omics components associated with type 1 diabetes. These findings offer novel insights into the disease's etiology, diagnosis, and treatment.

摘要

背景

近年来,1型糖尿病的发病率一直在稳步上升,将其预防和治疗作为全球公共卫生倡议的核心重点。以往的孟德尔随机化(MR)研究调查了蛋白质组学与1型糖尿病之间的关系。因此,本研究旨在通过全面的多组学分析确定1型糖尿病的潜在治疗靶点。

方法

本研究主要采用MR方法,利用来自几个大规模、可公开获取的全基因组关联研究的遗传数据。在此框架内,我们应用两样本MR来评估五个组学成分与1型糖尿病之间的关系。最后,我们进行了各种敏感性分析和双向MR,以确保研究结果的稳健性和可靠性。

结果

逆方差加权法显示,经过错误发现率校正后,39种血浆蛋白和3种血浆蛋白比值与1型糖尿病存在显著关联。1型糖尿病的遗传预测风险范围从RBP2的0.05到FMNL1的394.51。此外,4-氯苯甲酸水平与1型糖尿病存在潜在关联。

结论

我们的研究确定了许多与1型糖尿病相关的组学成分。这些发现为该疾病的病因、诊断和治疗提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f374/12059444/9ba2c5a7583d/10.1177_20420188251337988-fig1.jpg

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